Enterprise software systems are typically sophisticated, large-scale systems that support many, e.g., hundreds or thousands, of concurrent users. Examples of enterprise software systems include financial planning systems, budget planning systems, order management systems, inventory management systems, sales force management systems, business intelligence tools, enterprise reporting tools, project and resource management systems, and other enterprise software systems.
Many enterprise performance management and business planning applications require a large base of users to enter data that the software then accumulates into higher level areas of responsibility in the organization. Moreover, once data has been entered, it must be retrieved to be utilized. The system may perform mathematical calculations on the data, combining data submitted by many users. Using the results of these calculations, the system may generate reports for review by higher management. Often these complex systems make use of multidimensional data sources that organize and manipulate the tremendous volume of data using data structures referred to as data cubes. Each data cube, for example, includes a plurality of hierarchical dimensions having levels and members for storing the multidimensional data.
Business intelligence (BI) systems may be used to provide insights into such collections of enterprise data. A BI system may use a manually created metadata model to organize and describe large bodies of enterprise data to support useful business intelligence tools. A metadata model may contain descriptions of the structure and context of the data, and support queries of the data with the BI system. Typically, a BI system may use a metadata model that may be created manually by a data modeler to describe the data. The metadata model may contain descriptions of the structure and nature of the data, such as portions of the data that are categories and portions of the data that are numeric metrics, for example. Such descriptions of the data may provide enough context to the BI system to allow it to create useful queries. BI systems also now typically incorporate data from various unmodeled collections of data, such as spreadsheets and comma-separated values (CSV) files.